Abstract: Methods and systems for detection of an endpoint of a substrate process are provided. A set of machine learning models are trained to provide a metrology measurement value associated with a particular type of metrology measurement for a substrate based on spectral data collected for the substrate. A respective machine learning model is selected to be applied to future spectral data collected during a future substrate process for a future substrate in view of a performance rating associated with the particular type of metrology measurement. Current spectral data is collected during a current process for a current substrate and provided as input to the respective machine learning model. An indication of a respective metrology measurement value corresponding to the current substrate is extracted from one or more outputs of the trained machine learning model.

Abstract: Methods and systems for detection of an endpoint of a substrate process are provided. A set of machine learning models are trained to provide a metrology measurement value associated with a particular type of metrology measurement for a substrate based on spectral data collected for the substrate. A respective machine learning model is selected to be applied to future spectral data collected during a future substrate process for a future substrate in view of a performance rating associated with the particular type of metrology measurement. Current spectral data is collected during a current process for a current substrate and provided as input to the respective machine learning model. An indication of a respective metrology measurement value corresponding to the current substrate is extracted from one or more outputs of the trained machine learning model.

Abstract: A machine learning model trained to provide metrology measurements for a substrate is provided. Training data generated for a prior substrate processed according to a prior process is provided to train the model. The training data includes a training input including a subset of historical spectral data extracted from a normalized set of historical spectral data collected for the prior substrate during the prior process. The subset of historical spectral data includes an indication of historical spectral features associated with a particular type of metrology measurement. The training data also includes a training output including a historical metrology measurement obtained for the prior substrate, the historical metrology measurement associated with the particular type of metrology measurement. Spectral data is collected for a current substrate processed according to a current process.

Abstract: A networked computer system comprising a computer or a server having a computer software application for generating a paperless delivery receipt for a shipment by a carrier, a mobile device for downloading the paperless delivery receipt, and a computer user interface on the mobile device for capturing an electronic signature associated with the paperless delivery receipt.

Abstract: The present inventors have developed an accurate method for forming a plurality of images on a substrate. The present method provides an improved pattern replication technique that provides submicron resolution, for example 20 nm or less, especially 10 nm or less. The method may involve moving a structured beam of energetic radiation across a target substrate. The motion of an image of the template mask on the substrate is achieved by tilting a mask and substrate assembly relative to the axis of the incident beam. The technique does not require high precision motion of the template mask relative to the target substrate. The energetic radiation may comprise energetic particles. The technique is insensitive to particle energy and can be applied to uncharged, neutral particles.

Abstract: The present inventors have developed an accurate method for forming a plurality of images on a substrate. The present method provides an improved pattern replication technique that provides submicron resolution, for example 20 nm or less, especially 10 nm or less. The method may involve moving a structured beam of energetic radiation across a target substrate. The motion of an image of the template mask on the substrate is achieved by tilting a mask and substrate assembly relative to the axis of the incident beam. The technique does not require high precision motion of the template mask relative to the target substrate. The energetic radiation may comprise energetic particles. The technique is insensitive to particle energy and can be applied to uncharged, neutral particles.